The proposed research will consider how influences on infant and child mortality vary at different ages of the child and how they change with socioeconomic development. Its premise is that demographic and socioeconomic variables affect mortality through mediating behavioral factors. By appropriate modelling of these causal mechanisms, it aims to clarify the reasons underlying mortality trends and differentials in developing countries. Specifically, the research will consider how socioeconomic variables influence parents' behaviors that affect their children's health, growth, and survival. It will investigate, in particular, decisions concerning feeding and health care utilization, using a multidisciplinary framework that views these behaviors as responses to perceived costs and benefits, subject to biomedical, time, and income constraints. It will then assess the consequences of these behaviors for children's health and survival, recognizing that the behaviors and health outcomes may be jointly determined. It will study the relative importance of influences on family health behavior and on child health outcomes at different sub-periods of infancy and childhood and at different stages of socioeconomic development. The research will explicitly investigate the reasons for declines and urban-rural differentials in infant and child mortality and in breastfeeding. The study will use rich, comparable data on individuals and households in two very different countries--Guatemala and Malaysia. The datasets are (1) the INCAP Rand Guatemala Survey, (2) the INCAP Longitudinal Study, and (3) the Malaysian Family Life Survey. The Guatemalan datasets will be combined into a single database in this project. This database documents, in unusual detail, families' socioeconomic and demographic characteristics, their children's feeding and health care utilization, and the children's nutritional status, morbidity, and mortality. The research will compare influences on health behaviors and outcomes in Guatemala and Malaysia, providing a test of the applicability of our framework in two very different settings. Multivariate statistical techniques, including hazard models with time-varying covariates, will be used in the empirical analyses.